原发性中枢神经系统恶性淋巴瘤MR表现及其病理学基础

目的 研究原发性中枢神经系统恶性淋巴瘤(PCNSL)的MR表现及其病理学基础。方法 分析13例手术病理证实的原发性中枢神经系统恶性淋巴瘤的临床病理及MR表现。结果 13例中单发肿瘤4例，多发肿瘤9例，共计36个病灶。13例病变均累及幕上，其中8例病灶位于深部脑白质近脑室旁。肿瘤平均最大径为3．2cm。T1WI略低信号28个，T2WI等信号24个。28个病灶呈均匀强化。肿瘤水肿及占位效应相对较轻。2例PCNSL行MR动态增强扫描，早期强化均不明显，时间-信号强度曲线呈缓慢上升型。病理上肿瘤细胞弥漫分布，瘤细胞大小较一致，细胞质少，细胞核大，染色质颗粒粗，可见瘤细胞围绕血管呈袖套样浸润，少见明显的出血及片状坏死，未见钙化，病理均为非霍奇金淋巴瘤。结论 原发性中枢神经系统恶性淋巴瘤的病理基础决定其MR增强形态、占位程度以及肿瘤发生部位具有一定特征，运用不同的MR影像学检查方法和技术，在多数情况下可以做出术前正确诊断。     

Breast MR segmentation and lesion detection with cellular neural networks and 3D template matching

A novel fully automated system is introduced to facilitate lesion detection in dynamic contrast-enhanced, magnetic resonance mammography (DCE-MRM). The system extracts breast regions from pre-contrast images using a cellular neural network, generates normalized maximum intensity-time ratio (nMITR) maps and performs 3D template matching with three layers of 12x12 cells to detect lesions. A breast is considered to be properly segmented when relative overlap >0.85 and misclassification rate <0.10. Sensitivity, false-positive rate per slice and per lesion are used to assess detection performance. The system was tested with a dataset of 2064 breast MR images (344slicesx6 acquisitions over time) from 19 women containing 39 marked lesions. Ninety-seven percent of the breasts were segmented properly and all the lesions were detected correctly (detection sensitivity=100%), however, there were some false-positive detections (31%/lesion, 10%/slice).     

Tumor characterization in small animals using magnetic resonance-guided dynamic contrast enhanced diffuse optical tomography

We present a magnetic resonance (MR)-guided near-infrared dynamic contrast enhanced diffuse optical tomography (DCE-DOT) system for characterization of tumors using an optical contrast agent (ICG) and a MR contrast agent [Gd-diethylenetriaminepentaacetic acid (DTPA)] in a rat model. Both ICG and Gd-DTPA are injected and monitored simultaneously using a combined MRI-DOT system, resulting in accurate co-registration between two imaging modalities. Fisher rats bearing R3230 breast tumor are imaged using this hybrid system. For the first time, enhancement kinetics of the exogenous contrast ICG is recovered from the DCE-DOT data using MR anatomical a priori information. As tumors grow, they undergo necrosis and the tissue transforms from viable to necrotic. The results show that the physiological changes between viable and necrotic tissue can be differentiated more accurately based on the ICG enhancement kinetics when MR anatomical information is utilized.     

A use of a neural network to evaluate contrast enhancement curves in breast magnetic resonance images

For the diagnosis of breast cancer using magnetic resonance imaging (MRI), one of the most important parameters is the analysis of contrast enhancement. A threedimensional MR sequence is applied before and five times after bolus injection of paramagnetic contrast medium (Gd-DTPA). The dynamics of absorption are described by a time/intensity enhancement curve, which reports the mean intensity of the MR signal in a small region of interest (ROI) for about 8 minutes after contrast injection. The aim of our study was to use an artificial neural network to automatically classify the enhancement curves as “benign” or “malignant.” We used a classic feed-forward back-propagation neural network, with three layers: five input nodes, two hidden nodes, and one output node. The network has been trained with 26 pathologic curves (10 invasive carcinoma [K], two carcinoma-in-situ [DCIS], and 14 benign lesion [B]). The trained network has been tested with 58 curves (36 K, one DCIS, 21 B). The network was able to correctly identify the test curves with a sensitivity of 76% and a specificity of 90%. For comparison, the same set of curves was analyzed separately by two radiologists (a breast MR expert and a resident radiologist). The first correctly interpreted the curves with a sensitivity of 76% and a specificity of 90%, while the second scored 59% for sensitivity and 90% for specificity. These results demonstrate that a trained neural network recognizes the pathologic curves at least as well as an expert radiologist. This algorithm can help the radiologist attain rapid and affordable screening of a large number of ROIs. A complete automatic computer-aided diagnosis support system should find a number of potentially interesting ROIs and automatically analyze the enhancement curves for each ROI by neural networks, reporting to the radiologist only the potentially pathologic ROIs for a more accurate, manual, repeated evaluation.     

Characterization of oligodendrogliomas using short echo time 1H MR spectroscopic imaging

Oligodendroglial tumors may not be distinguished easily from other brain tumors based on clinical presentation and magnetic resonance imaging (MRI) alone. Identification of these tumors however may have therapeutic consequences. The purpose of this study was to characterize and identify oligodendrogliomas by their metabolic profile as measured by (1)H MR spectroscopic imaging (MRSI). Fifteen patients with oligodendroglial tumors (eight high-grade oligodendrogliomas, seven low-grade oligodendrogliomas) underwent MRI and short echo time (1)H MRSI examinations. Five main metabolites found in brain MR spectra were quantified and expressed as ratios of tumor to contralateral white matter tissue. The level of lipids plus lactate was also assessed in the tumor. For comparison six patients with a low grade astrocytoma were also included in the study. The metabolic profile of oligodendrogliomas showed a decreased level of N-acetylaspartate and increased levels of choline-containing compounds and glutamine plus glutamate compared with white matter. The level of glutamine plus glutamate was significantly higher in low-grade oligodendrogliomas than in low-grade astrocytomas and may serve as a metabolic marker in diagnosis and treatment planning. In high-grade oligodendrogliomas large resonances of lipids plus lactate were observed in contrast to low-grade tumors.     

Serial evaluation of patients with brain tumors using volume MRI and 3D 1H MRSI.

Patients with brain tumors are routinely monitored for tumor progression and response to therapy using magnetic resonance imaging (MRI). Although serial changes in gadolinium enhancing lesions provide valuable information for making treatment decisions, they do not address the fate of non-enhancing lesions and are unable to distinguish treatment induced necrosis from residual or recurrent tumor. The introduction of a non-invasive methodology, which could identify an active tumor more reliably, would have a major impact upon patient care and evaluation of new therapies. There is now compelling evidence that magnetic resonance spectroscopic imaging (MRSI) can provide such information as an add-on to a conventional MRI examination. We discuss data acquisition and analysis procedures which are required to perform such serial MRI-MRSI examinations and compare their results with data from histology, contrast enhanced MRI, MR cerebral blood volume imaging and FDG-PET. Applications to the serial assessment of response to therapy are illustrated by considering populations of patients being treated with brachytherapy and gamma knife radiosurgery.     

Simultaneous in vivo dynamic contrast-enhanced magnetic resonance and scintigraphic imaging

In this study, we investigated the in vivo application of an integrated small-animal magnetic resonance (MR) and gamma-ray imaging system that consists of a semiconductor-based radiation detector, a parallel-hole collimator, and a specialized radiofrequency coil. Gadodiamide and (99m)Tc sestimibi agents were injected simultaneously into a mouse, and simultaneous dynamic contrast-enhanced MR and scintigraphic images of the kidneys were acquired. The time curves of both the MR signal intensity and radioactivity indicate a rapid uptake of the agents followed by a more gradual excretion, consistent with the previously reported literature. Our results demonstrate the feasibility of measuring multiple biological processes at the same time using both MR contrast agents and radiotracers.     

Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma

Pseudoprogression (PsP) refers to treatment-related clinico-radiologic changes mimicking true progression (TP) that occurs in patients with glioblastoma (GBM), predominantly within the first 6 months after the completion of surgery and concurrent chemoradiation therapy (CCRT) with temozolomide. Accurate differentiation of TP from PsP is essential for making informed decisions on appropriate therapeutic intervention as well as for prognostication of these patients. Conventional neuroimaging findings are often equivocal in distinguishing between TP and PsP and present a considerable diagnostic dilemma to oncologists and radiologists. These challenges have emphasized the need for developing alternative imaging techniques that may aid in the accurate diagnosis of TP and PsP. In this review, we encapsulate the current state of knowledge in the clinical applications of commonly used metabolic and physiologic magnetic resonance (MR) imaging techniques such as diffusion and perfusion imaging and proton spectroscopy in distinguishing TP from PsP. We also showcase the potential of promising imaging techniques, such as amide proton transfer and amino acid-based positron emission tomography, in providing useful information about the treatment response. Additionally, we highlight the role of “radiomics”, which is an emerging field of radiology that has the potential to change the way in which advanced MR techniques are utilized in assessing treatment response in GBM patients. Finally, we present our institutional experiences and discuss future perspectives on the role of multiparametric MR imaging in identifying PsP in GBM patients treated with “standard-of-care” CCRT as well as novel/targeted therapies.     

A study on the magnetic resonance imaging (MRI)-based radiation treatment planning of intracranial lesions

The aim of this study is to develop a magnetic resonance imaging (MRI)-based treatment planning procedure for intracranial lesions. The method relies on (a) distortion correction of raw magnetic resonance (MR) images by using an adaptive thresholding and iterative technique, (b) autosegmentation of head structures relevant to dosimetric calculations (scalp, bone and brain) using an atlas-based software and (c) conversion of MR images into computed tomography (CT)-like images by assigning bulk CT values to organ contours and dose calculations performed in Eclipse (Philips Medical Systems). Standard CT + MRI-based and MRI-only plans were compared by means of isodose distributions, dose volume histograms and several dosimetric parameters. The plans were also ranked by using a tumor control probability (TCP)-based technique for heterogeneous irradiation, which is independent of radiobiological parameters. For our 3 T Intera MRI scanner (Philips Medical Systems), we determined that the total maximum image distortion corresponding to a typical brain study was about 4 mm. The CT + MRI and MRI-only plans were found to be in good agreement for all patients investigated. Following our clinical criteria, the TCP-based ranking tool shows no significant difference between the two types of plans. This indicates that the proposed MRI-based treatment planning procedure is suitable for the radiotherapy of intracranial lesions.     

Automatic identification and classification of characteristic kinetic curves of breast lesions on DCE-MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast is being used increasingly in the detection and diagnosis of breast cancer as a complementary modality to mammography and sonography. Although the potential diagnostic value of kinetic curves in DCE-MRI is established, the method for generating kinetic curves is not standardized. The inherent reason that curve identification is needed is that the uptake of contrast agent in a breast lesion is often heterogeneous, especially in malignant lesions. It is accepted that manual region of interest selection in 4D breast magnetic resonance (MR) images to generate the kinetic curve is a time-consuming process and suffers from significant inter- and intraobserver variability. We investigated and developed a fuzzy c-means (FCM) clustering-based technique for automatically identifying characteristic kinetic curves from breast lesions in DCE-MRI of the breast. Dynamic contrast-enhanced MR images were obtained using a T1-weighted 3D spoiled gradient echo sequence with Gd-DTPA dose of 0.2 mmol/kg and temporal resolution of 69 s. FCM clustering was applied to automatically partition the signal-time curves in a segmented 3D breast lesion into a number of classes (i.e., prototypic curves). The prototypic curve with the highest initial enhancement was selected as the representative characteristic kinetic curve (CKC) of the lesion. Four features were then extracted from each characteristic kinetic curve to depict the maximum contrast enhancement, time to peak, uptake rate, and washout rate of the lesion kinetics. The performance of the kinetic features in the task of distinguishing between benign and malignant lesions was assessed by receiver operating characteristic analysis. With a database of 121 breast lesions (77 malignant and 44 benign cases), the classification performance of the FCM-identified CKCs was found to be better than that from the curves obtained by averaging over the entire lesion and similar to kinetic curves generated from regions drawn within the lesion by a radiologist experienced in breast MRI.     

超微超顺磁性氧化铁的制备及其对家兔毒性作用的研究

目的：制备超微超顺磁性氧化铁（USPIO），观察其对家兔的毒性作用，并研究其物理、磁学性质，探讨其作为磁共振阴性对比剂的可能性。方法：采用化学共沉淀法制备四氧化三铁（Fe3O4）纳米粒，采用X射线粉末衍射仪、透射电镜、磁强计及1．5T超导型磁共振仪等测定其相关理化指标。选取家兔20只，随机分为实验组（10只）和对照组（10只），实验组按1．25ml／kg耳缘静脉注射样品、对照组按1．25ml／kg耳缘静脉给予生理盐水。给药后于饲养2周末，检测其血清主要生化指标、观察主要脏器的病理学改变。并行MR检查观察实验组肝、脾的增强效果。结果：成功制备USPIO，核心粒径小于10nm，饱和磁化强度为47．2emu／g。给药后饲养2周，家兔无死亡。给药2周末予MR检查，实验组肝、脾在T2WI信号降低，对照组肝、脾在T2WI信号未见降低；两组家兔各项血清生化指标比较，差异均无统计学意义（P〉0．05）；其肝、脾组织进行普鲁士蓝染色，实验组家兔肝、脾内分布少许铁蓝色颗粒，而对照组均无铁蓝色颗粒。结论：采用化学共沉淀法制备的USPIO符合作为磁共振成像阴性对比剂的要求，通过给药家兔血清学、病理组织学及磁共振成像检查，说明USPIO生物相容性较好且毒性低，可作为磁共振的阴性对比剂用于肝、脾等部位磁共振成像。     

Evaluation of ectopic pregnancy by magnetic resonance imaging.

Patients (n = 37) suspected of ectopic pregnancy were prospectively evaluated with magnetic resonance (MR) imaging to assess the capability of MR imaging in the diagnosis of ectopic pregnancy. Five levels of confidence were defined: diagnostic, suspicious, equivocal, questionable, and negative. Tubal wall enhancement and presence of tubal haematoma or gestational sac-like structure were considered diagnostic findings. There were 21 diagnostic, two suspicious, eight equivocal, and six negative findings. MR findings were compared with the surgical findings in 18 patients. Surgical confirmation was obtained in 12 diagnostic, two suspicious, and four equivocal studies. Using the MR diagnostic criteria for tubal pregnancy, MR had 12 true positive, three true negative, three false negative, and no false positive results for the diagnosis of tubal pregnancy. Retrospective analysis of the signal intensity of haematoma and ascites was performed for these 18 surgically confirmed cases. The predominant signal intensity of tubal haematoma was an intermediate signal on T1-weighted image (WI) and a low signal on T2WI. Ascites showed signal intensity higher than that of urine on T1WI in 100% of 13 cases. In conclusion, MR imaging with use of intravenous contrast material allows a specific diagnosis of tubal pregnancy, recognizing tubal wall enhancement and fresh tubal haematoma.     

基于SE序列的MR图像权重计算方法

目的：探究一种基于SE序列的MR图像权重计算方法，为判定sE加权像提供更加科学及准确的判定依据。方法：提出一种计算两种生物组织的质子密度特性差异、纵向弛豫时间特性差异及横向弛豫时间特性差异各自对磁共振图像对比度的贡献比例方法，首先，将磁共振图像对比度公式进行等量变换，建立SE序列权重对比度数学关系式；其次，对该关系式进行对数变换，在对数坐标下，乘性权重因子转化为加性权重因子；最后，利用比例计算公式计算生物组织的三种特性差异各自对磁共振图像的贡献比例。结果：利用医用核磁共振仪器，通过对重复时间及回波时间不同设置后，获得两幅关于白质和灰质的MR图像，然后利用本文介绍的基于SE序列的MR图像权重计算方法，获得质子密度特性差异、纵向弛豫时间特性差异及横向弛豫时间特性差异各自对MR图像对比度贡献比例，并显示于这两幅MR图像上．可定量判定SE加权像。结论：通过本文介绍的基于sE序列的MR图像权重计算方法，对精确判定磁共振SE加权像有极大的帮助。     

Identification of MRI and 1H MRSI parameters that may predict survival for patients with malignant gliomas

Although MR imaging (MRI) and MR spectroscopic imaging (MRSI) have been applied in the diagnosis and treatment planning for brain tumors, their prognostic significance has not yet been determined. The goal of this study was to identify pre-treatment MRI and MRSI parameters for patients with malignant glioma that may be useful in predicting survival. Two populations of patients with newly-diagnosed malignant glioma were examined with MRI and three-dimensional proton ((1)H) MRSI. Thirty-nine patients (22 grade 3 and 17 glioblastoma multiforme, GBM) were studied prior to surgery, and 33 GBM patients were studied after surgery but prior to treatment with radiation and chemotherapy. Signal intensities of choline (Cho), creatine (Cr), N-acetyl aspartate (NAA), and lactate/lipid (LL) were estimated from the spectra. Recursive partitioning methods were applied to parameters that included age, histological grade, MRI and MRSI variables to generate survival trees. Patients were grouped into high and low risk categories and the corresponding Kaplan-Meier curves were plotted for comparison between groups. The parameters that were selected by recursive partitioning as being predictive of poor outcome were older age, larger contrast enhancement, higher Cho-to-Cr, higher Cho-to-NAA, higher LL and lower Cr-to-NAA abnormalities. The survival functions were significantly different between the sub-groups of patients obtained from the survival tree for both pre-surgery and post-surgery data. The results of this study suggest that pre-treatment MRI and three-dimensional (1)H-MRSI provide information that predicts outcome for patients with malignant gliomas and have drawn attention to variables that should be examined prospectively in future studies using these techniques.     

Use of BANG polymer gel for dose measurements in a 68 MeV proton beam

BANG polymer gel dosimetry using magnetic resonance imaging (MRI) was applied to an ophthalmologic 68 MeV proton beam. The object was to examine the use of BANG gel for the verification of proton fields in eye tumor therapy and to explore the applicability of polymer gel dosimetry in proton therapy under practical aspects. The gel phantoms were irradiated with monoenergetic and modulated proton beams. MRI analysis was carried out at clinical 1.5 and 3 T MR scanners. At constant LET, results show a linear relationship between spin-spin relaxation rates and dose. However, depth dose curves in BANG gel reveal a quenching of the Bragg maximum due to LET effects. The dose response of the gel for monoenergetic protons and spread-out depth dose distributions can be calculated based on ionization chamber measurements. Experiment and calculations show good agreement and indicate that BANG polymer gels might become a valuable tool in proton therapy quality assurance.     

Long-term multimodal imaging of tumor draining sentinel lymph nodes using mesoporous silica-based nanoprobes

The imaging of sentinel lymph nodes (SLNs), the first defense against primary tumor metastasis, has been considered as an important strategy for noninvasive tracking tumor metastasis in clinics. In this study, we report the development and application of mesoporous silica-based triple-modal nanoprobes that integrate multiple functional moieties to facilitate near-infrared optical, magnetic resonance (MR) and positron emission tomography (PET) imaging. After embedding near-infrared dye ZW800, the nanoprobe was labeled with T(1) contrast agent Gd(3+) and radionuclide (64)Cu through chelating reactions. High stability and long intracellular retention time of the nanoprobes was confirmed by in vitro characterization, which facilitate long-term in vivo imaging. Longitudinal multimodal imaging was subsequently achieved to visualize tumor draining SLNs up to 3 weeks in a 4T1 tumor metastatic model. Obvious differences in uptake rate, amount of particles, and contrast between metastatic and contra-lateral sentinel lymph nodes were observed. These findings provide very helpful guidance for the design of robust multifunctional nanomaterials in SLNs' mapping and tumor metastasis diagnosis.     

Iron oxide nanoparticle-containing microbubble composites as contrast agents for MR and ultrasound dual-modality imaging

Magnetic resonance (MR) and ultrasound (US) imaging are widely used diagnostic modalities for various experimental and clinical applications. In this study, iron oxide nanoparticle-embedded polymeric microbubbles were designed as multi-modal contrast agents for hybrid MR-US imaging. These magnetic nano-in-micro imaging probes were prepared via a one-pot emulsion polymerization to form poly(butyl cyanoacrylate) microbubbles, along with the oil-in-water (O/W) encapsulation of iron oxide nanoparticles in the bubble shell. The nano-in-micro embedding strategy was validated using NMR and electron microscopy. These hybrid imaging agents exhibited strong contrast in US and an increased transversal relaxation rate in MR. Moreover, a significant increase in longitudinal and transversal relaxivities was observed after US-induced bubble destruction, which demonstrated triggerable MR imaging properties. Proof-of-principle in?vivo experiments confirmed that these nanoparticle-embedded microbubble composites are suitable contrast agents for both MR and US imaging. In summary, these magnetic nano-in-micro hybrid materials are highly interesting systems for bimodal MR-US imaging, and their enhanced relaxivities upon US-induced destruction recommend them as potential vehicles for MR-guided US-mediated drug and gene delivery.     

Long-term in vivo magnetic resonance imaging tracking of endothelial progenitor cells transplanted in rat ischemic limbs and their angiogenic potential

Stem cell therapy has been used to repair ischemic tissues in the limbs, in myocardial infarctions, and in the brain. To understand the mechanisms of healing, a contrast agent capable of inducing sufficient magnetic resonance (MR) contrast would be useful in providing fundamental information about the cell migration and incorporation into the ischemic tissue. A magnetic resonance imaging contrast agent composed of dextran and gadolinium chelate was synthesized. Hydroxyl groups of dextran were activated with 1,1'-carbonylbis-1H-imidazole and reacted with propanediamine to obtain aminated dextran. This modified polymer was then reacted with mono-N-succinimidyl 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetate, then with fluorescein isothiocyanate, and finally reacted with gadolinium chloride solution (Dex-DOTA-Gd3(+)). Endothelial progenitor cells (EPCs) were selected as a stem cell model for magnetic resonance imaging tracking. Cells were isolated from the bone marrow harvested from the femurs and tibias of rats. Dex-DOTA-Gd3(+) was then introduced into the EPCs by electroporation. The intracellular stability and cytotoxicity of Dex-DOTA-Gd3(+) were evaluated in vitro. Dex-DOTA-Gd3(+)-labeled EPCs were transplanted into a rat model of ischemic limb, and MR images were acquired. Dex-DOTA-Gd3(+) was found to efficiently label EPCs over a long duration without significant cytotoxicity. This provides an MR signal sufficient for tracking the EPCs intramuscularly injected into the limb.     

New magnetic-resonance-imaging-visible poly(ε-caprolactone)-based polyester for biomedical applications

A great deal of effort has been made since the 1990s to enlarge the field of magnetic resonance imaging. Better tissue contrast, more biocompatible contrast agents and the absence of any radiation for the patient are some of the many advantages of using magnetic resonance imaging (MRI) rather than X-ray technology. But implantable medical devices cannot be visualized by conventional MRI and a tool therefore needs to be developed to rectify this. The synthesis of a new MRI-visible degradable polymer is described by grafting an MR contrast agent (DTPA-Gd) to a non-water-soluble, biocompatible and degradable poly(ε-caprolactone) (PCL). The substitution degree, calculated by (1)H nuclear magnetic resonance and inductively coupled plasma-mass spectrometry, is close to 0.5% and proves to be sufficient to provide a strong and clear T1 contrast enhancement. This new MRI-visible polymer was coated onto a commercial mesh for tissue reinforcement using an airbrush system and enabled in vitro MR visualization of the mesh for at least 1 year. A stability study of the DTPA-Gd-PCL chelate in phosphate-buffered saline showed that a very low amount of gadolinium was released into the medium over 52 weeks, guaranteeing the safety of the device. This study shows that this new MRI-visible polymer has great potential for the MR visualization of implantable medical devices and therefore the post-operative management of patients.